fix negative variance for constant variables (ecmwf#148)

* variance is negative for constant variables, due to rounding errors. Setting it to zero when it is negative

* Update CHANGELOG.md

CHANGELOG.md

@@ -13,6 +13,7 @@ Keep it human-readable, your future self will thank you!
 ## Changed
 
 - Fix metadata serialization handling of numpy.integer (#140)
+- Fix negative variance for constant variables (#148)
 - Fix cutout slicing of grid dimension (#145)
 
 ### Added

src/anemoi/datasets/create/functions/__init__.py

@@ -22,6 +22,7 @@ def assert_is_fieldlist(obj):
 def import_function(name, kind):
 
     from anemoi.transform.filters import filter_registry
+    from anemoi.transform.sources import source_registry
 
     name = name.replace("-", "_")
 
@@ -45,7 +46,20 @@ def import_function(name, kind):
         if filter_registry.lookup(name, return_none=True):
 
             def proc(context, data, *args, **kwargs):
-                return filter_registry.create(name, *args, **kwargs)(data)
+                filter = filter_registry.create(name, *args, **kwargs)
+                filter.context = context
+                # filter = filter_registry.create(context, name, *args, **kwargs)
+                return filter.forward(data)
+
+            return proc
+
+    if kind == "sources":
+        if source_registry.lookup(name, return_none=True):
+
+            def proc(context, data, *args, **kwargs):
+                source = source_registry.create(name, *args, **kwargs)
+                # source = source_registry.create(context, name, *args, **kwargs)
+                return source.forward(data)
 
             return proc
 

src/anemoi/datasets/create/statistics/__init__.py

@@ -98,7 +98,7 @@ def fix_variance(x, name, count, sums, squares):
 
     variances = squares / count - mean * mean
     assert variances.shape == squares.shape == mean.shape
-    if all(variances >= 0):
+    if np.all(variances >= 0):
         LOG.warning(f"All individual variances for {name} are positive, setting variance to 0.")
         return 0
 
@@ -108,7 +108,7 @@ def fix_variance(x, name, count, sums, squares):
     #     return 0
 
     LOG.warning(f"ERROR at least one individual variance is negative ({np.nanmin(variances)}).")
-    return x
+    return 0
 
 
 def check_variance(x, variables_names, minimum, maximum, mean, count, sums, squares):